http://www.worldbank.org/commodities
SPECIAL FOCUS
Persistence of commodity shocks
C O M M O D I T Y M A R K E T S O U T LO O K | O C TO B E R 2 0 2 0
S P EC IAL FO CU S
Persistence of commodity shocks
Almost two-thirds of emerging market and developing economies (EMDEs) and three-quarters of low-income
countries rely heavily on commodity extraction and export. This can put their economies at the mercy of global
commodity markets, which are prone to shocks. The most recent example is the impact of COVID-19
pandemic. To the extent such shocks are transitory, commodity-exporting EMDEs can buffer their impact on
local economies; to the extent these shocks are permanent, policy makers in these countries need to facilitate a
smooth adjustment to a new economic reality. Based on an analysis of 27 commodities during 1970-2019, this
Special Focus finds that transitory and permanent shocks contributed almost equally to commodity price
variations, although with wide heterogeneity. Permanent shocks accounted for two-thirds of the variability in
annual agricultural commodity prices but less than half of the variability in base metals prices. For energy
prices, permanent shocks have trended upward, for agricultural prices, downwards, and for metals prices, flat.
The volatility triggered in April-October by the COVID-19 pandemic appears to constitute a series of largely
transitory shocks for oil prices.
Introduction
The COVID-19 pandemic delivered an enormous
shock to the global economy and led to the
deepest global recession since the second world
war, by far surpassing the recession in 2009 that
was triggered by the global financial crisis (World
Bank 2020a). The pandemic impacted commodity markets as well, but its effect on prices has been
heterogenous (World Bank 2020b). Between
January and April 2020 energy prices dropped
nearly 60 percent while metals and food prices
declined by 15 and 10 percent, respectively (figure
SF.1). Metal prices recovered in response to
supply shocks and a quicker-than-expected pickup
in China’s industrial activity, and food prices
stabilized as concerns about restrictive policy
measures faded. However, the impact of the
demand shock on the oil market may last much
longer.1
Commodity
price
movements
explain
considerable fluctuations in economic activity,
particularly in EMDEs (Aguiar and Gopinath
2007; Kose 2002). Policy makers can smooth
some of these fluctuations with policy stimulus or
1 According to BP (2020), 2019 may have been the year during
which global oil consumption peaked, marking a considerable revision to earlier projections which placed the “peak demand” year in
the early 2030s. For example, IEA (2019) projected that global oil
consumption would plateau around 2030. Peak demand discussions,
which emerged after the 2014 price collapse (Dale and Fattouh
2018), replaced the “peak oil” supply debate of the early 2010s
(Helbling et al. 2011; Kumhof and Muir 2014).
contraction—provided commodity price movements are temporary. For longer lasting shocks,
policy makers need to facilitate their economies’
smooth adjustment to a new normal.
Transitory shocks can originate from recessions,
such as the 2009 global financial crisis and the
1997 East Asian financial crises (both of which
impacted a wide range of commodities), trade
tensions (such as in 2018-19 and of special
relevance to metals and soybeans) or bans on grain
exports during 2007 and 2011 (World Bank
2019). They can also arise from adverse weather
conditions, most common to agriculture, such as
El Niño and La Niña episodes or drought-related
production shortfalls (such as grains in 1995 and
coffee in 1975 and 1985). Transitory shocks can
also result from accidents (2019 Vale accident in
Brazil which disrupted iron ore supplies), conflicts
(the first Gulf war, when Iraq/Kuwait oil
production was halted), or terrorist attacks (on the
Saudi oil facilities in 2019, which halted oil
exports temporarily) (World Bank 2019).
Shocks can also exert a permanent impact on
commodity markets. For example, the shale
technology shock in the natural gas and oil
industries rendered the United States a net energy
exporter in 2019, for the first time since 1952
(EIA 2020). The biotechnology shock of the
1990s increased crop productivity by more than
20 percent (Klümper and Qaim 2014). Policy
shocks can also have long-lasting impacts on
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S P EC IAL FO CU S
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FIGURE SF.1 Commodity price indexes
Commodity prices have been impacted differently by COVID-19. Energy
prices, which declined more than 60 percent from January to April 2020,
were still 32 percent lower in September. Metals and food prices were
impacted much less and have returned to pre-pandemic levels. The longterm effects of shocks on prices also varies across commodities.
A. Energy and metals, monthly
C. Energy and metals, annual
B. Fertilizers and agriculture, monthly
D. Fertilizers and agriculture, annual
Source: World Bank.
A.B. Shaded areas denote the pandemic period: January 2020 (when the first human-to-human
transmission was confirmed) to September 2020 (last observation of the sample).
C.D. The indexes have been deflated by the U.S. CPI. Last observation is 2020.
Click here to download charts and data.
commodity prices. Examples include government
efforts to encourage biofuel production, which
caused a 4 percent shift of global land from food
to biofuel production (Rulli et al. 2016);
interventions in agricultural markets by most
OECD countries, which have been shown to have
long term downward pressures on food prices
(Aksoy and Beghin 2004); and OPEC’s decisions
to reduce oil supplies (Kaufmann et al. 2004).
Shocks, especially those related to energy markets,
often propagate succeeding shocks. For example,
the COVID-19 oil demand shock, which caused
an estimated 10 percent decline in oil consumption during 2020, triggered a policy-driven supply
shock of similar magnitude by the OPEC-plus
group of a 9.7 mb/d oil production cut in April
2020.2 The oil price increases of the mid-2000s
(driven by EMDE demand, OPEC supply cuts,
and geopolitical concerns) rendered shale technology profitable, pushed up the costs of food
production, and triggered biofuel policies. Following the oil price collapse of 2014, food production
costs declined, but production of shale (through
innovation and cost reduction) and biofuels
(diverted from food commodities) appear to have
a permanent character.
Earlier literature on commodity price movements
reached two broad conclusions: prices respond to
shocks differently (Cuddington 1992; Snider
1924), and price movements are dominated by
volatility rather than long-term trends (Cashin and
McDermott 2002; Deaton 1999). More recent
research, however, finds that commodity prices are
subject to long-term cyclical patterns, the so-called
supercycles (Cuddington and Jerrett 2008).
This Focus examines how transitory and
permanent shocks impact commodity price movements. Whereas the existing literature analyzes
price movements in the context of either supercycles or cyclical-versus-trend behavior, this
analysis allows for business- and medium-term
cycles in line with the macroeconomic literature.
Specifically, this Focus addresses the following
questions.
1) How much do transitory and permanent
shocks contribute to commodity price
variability?
2) How have transitory and permanent shocks
compared across commodities?
How much do transitory and
permanent shocks contribute
to commodity price variability?
Methodology. To decompose commodity price
movements into transitory and permanent
components, a novel frequency domain approach
is used that has thus far mostly been applied to
2 The demand plunge and production cuts following COVID-19
were the largest in history (see energy section).
C O M M O D I T Y M A R K E T S O U T LO O K | O C TO B E R 2 0 2 0
economic business cycles (Corbae, Ouliaris, and
Phillips 2002; Corbae and Ouliaris 2006). The
analysis rests on monthly data for 27 commodity
price series over the period 1970-2019. It includes
3 energy prices, 5 base- and 3 precious-metals
prices, 11 agricultural commodity prices (separated into annual and perennial crops) and 4
fertilizer prices.3 The transitory shocks consist of
three components—short-term fluctuations (that
unwind in less than 2 years); traditional business
cycles with frequency of 2-8 years, as are typically
associated with economic activity (Burns and
Mitchell 1946); and medium-term cycles with
periodicity of 8-20 years, which are often
associated with investment activity (Slade 1982).
The permanent shock component captures
movements with periodicity of more than 20
years—consistent with supercycles.
Permanent and transitory shocks account for
roughly equal shares. On average across
commodities, permanent shocks accounted for 47
percent of price variability. Of the remainder (i.e.,
transitory shocks), medium-term cycles accounted
for 32 percent of price variability and business
cycles for 17 percent. Only a small portion (4
percent) of price variability is due to shocks that
are unwound in less than two years. The large role
of the permanent component is in line with the
findings of research into commodity price
supercycles (Erten and Ocampo 2013; Fernández,
Schmitt-Grohé, and Uribe 2020). Furthermore,
the predominance of the medium-term cycle in
the transitory component is in line with recent
research that finds a greater role of medium-term
cycles than shorter business cycles in output
fluctuations or domestic financial cycles (Aldasoro
et al. 2020; Cao and L’Huillier 2018).
3 The selection of commodity prices analyzed in this Focus was
based on a unique selection criteria by excluding commodities that
are close substitutes (e.g., selecting only one edible oil), they are no
longer economically important (e.g., hides and skins), or their prices
are not determined at an exchange (e.g., bananas). Following the
decomposition, the individual commodities were combined into six
groupings, based on the uses and production characteristics of commodities (see annex SF.1). A few studies that have used both individual commodity price series and indexes (e.g., Erten and Ocampo
2013; Jacks 2019; Ojeda-Joya, Jaulin-Mendez, and Bustos-Pelaez
2019) used data obtained directly from the International Monetary
Fund or World Bank commodity price databases without applying
selection criteria.
S P EC IAL FO CU S
The composition of transitory shocks differed
across commodities. Shocks at medium-term
frequency accounted for 55 and 27 percent of
price variability in energy and metals, respectively,
and only 14 percent for agriculture. In contrast,
business cycles accounted for 24 percent of price
variability for metals (figure SF.3). This greater
contribution of business cycle shocks to metal
commodity price fluctuations is in line with the
strong response of metal consumption to
industrial activity.4 Some of the commodities that
exhibited the highest contribution of transitory
shocks to price variability are used mainly within
the transportation sector. For example, nearly twothirds of crude oil is used for transportation, threequarters of natural rubber goes to tire manufacturing, and half of platinum is used in the
production of catalytic converters (World Bank
2020b).
These averages mask heterogeneity across
commodities. Transitory shocks were more
relevant to the price variation of industrial
commodities, while permanent shocks mattered
most in agricultural commodity price movements
(figure SF.2). For agricultural commodities,
permanent shocks accounted for two-thirds of
price variability, for metals (including base and
precious) they accounted for about 45 percent,
while for energy they accounted for less than 30
percent. Precious metals exhibited the largest
heterogeneity as a group, with gold prices driven
mostly by permanent shocks, silver driven equally
by permanent and transitory shocks, and platinum
exhibiting one of the highest shares of mediumterm cyclicality.
How have transitory and
permanent shocks evolved?
Transitory shocks
Almost all commodities have undergone three
medium-term cycles since 1970. The first
4 The relationship between metals prices and economic activity
has been well-established by numerous authors. See, for example,
Baffes, Kabundi, and Nagle (2020), Davutyan and Roberts (1994),
Labys, Achouch, and Terraza (1999), Labys, Lesourd, and Badillo
(1998), Marañon and Kumral (2019), Roberts (2009), Stuermer
(2017), and Tilton (1990).
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FIGURE SF.2 Price variation according to type of shock
Transitory and permanent shocks contribute almost equally, on average, to commodity price variation. However, these shares mask large
heterogeneity across commodities. Transitory shocks account for most of industrial commodity price variability, while permanent shocks
dominate agricultural commodity price movements.
A. Transitory and permanent shocks
Source: World Bank.
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medium-term cycle, which involved all
commodities, began in the early 1970s, peaked in
1978, and lasted until the mid-1980s. The second,
which peaked in 1994, was most pronounced in
base metals and agriculture (with similar duration
and amplitude to the first cycle) but did not
include energy commodities. The third cycle,
which again involved all commodities, began in
the early 2000s, peaked in 2010, and for some
commodities is still underway as of October 2020.
Crude oil’s “missing cycle” reflected offsetting
oil-specific shocks. Of the 27 commodities, crude
oil and natural gas (whose price is highly
correlated with oil) are the only commodities that
exhibited two, instead of three, medium-term
cycles. During the period spanning the second
medium-term cycle, the oil market was subjected
to three shocks.
Unconventional and offshore oil. New
production from unconventional sources of
oil came into the market (North Sea, Gulf of
Mexico, and Alaska). This was a result of
innovation and investment in response to the
high prices during the 1970s and early 1980s,
partly caused by OPEC supply restrictions
(World Bank 2020b).5
•
5
The three unconventional sources of oil—U.S. shale oil,
•
New spare capacity from the former Soviet
Union. Considerable spare capacity became
available in the global oil market following the
collapse of the Soviet Union. Prior to its
collapse, the Soviet economy featured both
inefficient production and energy-intensive
consumption (World Bank 2009).6
•
Substitution and demand contraction. High oil
prices during the late 1970s and early 1980s
led to substitution of oil by other energy
sources (especially coal and nuclear energy) in
electricity
generation.
Policy-mandated
efficiency standards in many OECD countries
lowered global demand for energy (Baffes,
Kabundi, and Nagle 2020).
Permanent shocks
The evolution of permanent shocks differed
markedly across commodity groups. For energy
commodities, the permanent shock component of
prices has trended upward, for agricultural and
Canadian oil sands, and biofuels—are also associated with the third
medium-term cycle (Baffes et al. 2015). In the first and third
medium-term cycles these unconventional sources of oil account for
about 10 percent of global oil supplies (measured at the end of the
cycle).
6 The collapse of the Soviet Union played a similar role in metals
and grain commodities. However, the increase in supplies of those
commodities was much smaller and gradual.
C O M M O D I T Y M A R K E T S O U T LO O K | O C TO B E R 2 0 2 0
fertilizer prices downward, and for most base
metals they have been largely trendless (figure
SF.4). The upward trend in energy prices may
reflect resource depletion and the largely trendless
nature of long-term metals price movements may
reflect the opposing forces of technological
innovation and resource depletion (see discussions
in Hamilton (2009) and Marañon and Kumral
(2019) on oil and metals, respectively). The
downward trend in permanent shocks to
agricultural prices is consistent with low income
elasticities of food commodities (Baffes and
Etienne 2016). Commodities with a history of
widespread policy interventions (cotton) or
subjected to international commodity agreements
(cocoa, coffee, crude oil, cotton, natural rubber,
and tin) followed a highly non-linear path (see
annex table SF.1).7
Annual agricultural price trends are highly
synchronized and differ from those of other
commodity groups. The contribution of
permanent shocks to annual agricultural price
variability (68 percent) is the highest among all six
commodity groups, and these permanent shocks
have evolved in a similar manner across annual
agricultural prices (figure SF.4).8 This similarity
reflects diffusion of shocks across commodities due
to
input
substitutability,
consumption
substitutability, and agricultural policies, which
are similar across most crops.
•
Input substitution. Annual agricultural
commodities tend to be farmed using the
same land, labor, machinery, and other
inputs. As a result, reallocation between
different annual crops from one year to
another prevents large price fluctuations in
individual crops. The impact of the restrictions in soybean imports by China from the
United States in 2008, was short-lived due to
7 Cotton has been subjected to a high degree of government
intervention by most major producers, including subsidies by the
United States and the EU, taxation of Sub-Saharan cotton producers,
and various types of policy interventions by Central Asian producers.
Throughout the 1960s and 1970s the cotton market was also
subjected to policy distortions by the Soviet Union (Baffes 2011).
8 Permanent shocks to agriculture have lasting effects on
economic activity in low income countries through their impact on
labor productivity (Dieppe, Francis, and Kindberg-Hanlon 2020).
S P EC IAL FO CU S
11
FIGURE SF.3 Transitory shocks
The business cycle component of transitory shocks is highest in metal,
consistent with the response of metals demand to industrial activity. There
have been three medium-term cycles, peaking in 1978, 1994, and 2020.
However, oil was subjected to only two medium-term cycles.
A. Contribution of business cycle
B. Medium-term cycle: energy and
metals
C. Medium-term cycle: fertilizers and
agriculture
D. Oil’s “missing” medium-term cycle
Source: World Bank.
A.-D. Authors’ calculations.
Click here to download charts and data.
land reallocation and trade diversion.
Separately, despite a policy-induced increase
in demand for maize, sugarcane, and edible
oils over the past two decades, price increases
in these three crops were in line with those of
other annual crops (e.g., rice and wheat) as
land was reallocated (World Bank 2019).9
•
Consumption substitution. Since annual crops
have overlapping uses, substitution in
consumption can dampen price fluctuations
in any one of them. In the example of import
9 Global demand for maize, a key feedstock for ethanol
production in the United States, doubled over the past two decades.
This compares with 26-28 percent increases in global demand for rice
and wheat, broadly in line with the 27 percent global population
growth over this period.
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FIGURE SF.4 Permanent shocks
The permanent shock component trends upward for energy and precious
metals, is nearly trendless for precious metals and fertilizers, and trends
downward for agriculture. These trends are homogenous for agriculture
but heterogenous for other groups.
A. Permanent shock, energy, and
metals
B. Permanent shocks, agriculture, and
fertilizers
markets, are renewed every few years and
apply to the same crops. Indeed, the 1985
Farm Bill reform in the U.S. and the 1992
Common Agricultural Policy reform in the
EU, applied to all commodities of the
respective programs (Baffes and De Gorter
2005).
Conclusion
C. Permanent shocks, selected metals
prices
D. Permanent shocks, selected
agricultural prices
Source: World Bank.
A.-D. Authors’ calculations.
Click here to download charts and data.
restrictions on soybeans discussed earlier,
soybean meal was substituted by maize for
animal use in China while soybean oil was
substituted by palm oil for human
consumption (World Bank 2019).10
•
Policy synchronization. Policy interventions for
agricultural markets tend to apply to the
entire sector and stay in place for several years,
even decades, with few or no changes. For
example, agricultural policies in the United
States and the EU, the world’s largest
producers in several agricultural commodity
10 The imposition of tariffs by China on U.S. soybean imports
resulted trade diversion. As China’s soybean imports from the U.S.
declined and increased from Brazil, the EU began importing more
from the U.S. and less from Brazil.
This Focus section finds that commodities are
subject to a multitude of different shocks.
Permanent shocks account for two-thirds of
agricultural price variability but less than half of
industrial commodity price variability over the
past fifty years. Meanwhile, business cycle shocks
play the largest role for base metals, reflecting their
heavy use in highly cyclical industries. For oil
prices, the COVID-19 pandemic constitutes a
series of temporary shocks, mainly at the business
cycle frequency. Permanent shocks have trended
upward for energy and precious metals prices but
downward for agricultural prices and have been
largely trendless for base metals prices. Annual
agricultural commodities were the commodity
group with the most homogeneous price trends,
reflecting high substitutability in inputs and uses,
and similar policies.
The heterogenous behavior of shocks suggests
a need for policy flexibility, especially in commodity-exporting
countries.
Countercyclical
macro-economic policies can help buffer the
impact of transitory shocks. Countries that depend
on exports of highly “cyclical” commodities that
are buffeted by frequent transitory shocks may
want to build fiscal buffers during the boom phase
and use them during the bust period in order to
support economic activity. In contrast, in
countries that rely heavily on commodities that are
subject to permanent shocks, structural policies
may be needed to facilitate adjustments to new
economic environments.
COMMODITY MARKETS OUTLOOK
I
OCTOBER 2020
SPECIAL FOCUS
ANNEX SF.1 Model and data
description
Decomposing commodity prices into cycles
and long-term trends
The real price of the commodity,
as the following sum:
t
example, because the edible oils are close
substitutes, only soybean oil is used in the
analysis.
•
Importance. Commodities whose share in
consumption diminished throughout the
sample (either because of changes in
preferences or substitution from synthetic
products) were not included in the sample.
Notable exclusions include wool, hides and
skins, sisal, and tobacco.
•
Price determination process. Prices are determined by market-based mechanisms, such as
on commodity exchanges or at auctions (in
the case of tea). Notable exclusions are iron
ore (its price used to be the outcome of a
negotiation process among key players of the
steel industry until 2005), bananas (its price
reflects quotations from a few large trading
companies), and sugar (policy interventions
reduce the significance of the world price
indicator), groundnuts (thinly traded commodity), and timber products (not traded on
exchanges).
, is expressed
pt  PCt + TCt[8,20] + TCt[2,8] + St
PCt , which represents the permanent component,
can be a linear trend, perhaps subjected to
structural breaks. (Alternatively, one could include
[8,20]
non-linearities.) TCt
denotes the medium-term
cycle with a periodicity of 8-20 years as proposed
by Blanchard ( 1997) and popularized by Co min
[2,8]
and Genier (2006). TCt
represents the business
cycle with a periodicity of 2-8 years, following
NBER' s traditional definition (Burns and Mitchell
1946). Lastly, St captures fluctu-ations with
periodicity of less than 2 years, which may reflect
short-term movement in economic activity or
other macroeconomic variables (such as exchange
rates and interest rates), seasonality or weather
patterns (in the case of agriculture), and ad hoc
policy shocks. These fluctuations are typically
studied within the context of VAR models
(Baumeister and Hamilton 2019; Kilian and
Murphy 2014) and GARCH models by utilizing
high-frequency data, focusing mostly on volatility
(Engle 1982). The decomposition is based on the
frequency domain methodology developed by
Corbae, Ouliaris, and Phillips (2002) and Corbae
and Ouliaris (2006).
The price data were taken from the W odd Bank's
world commodity price data system. The sample
covers 50 years: Januaty 1970 through December
2019 (600 observations). The prices, which are
reported in nominal U.S. dollar terms, were
deflated with the U.S. CPI (taken from the St.
Louis Federal Reserve Bank). Although the World
Bank covers more than 70 commodity price series,
this paper uses only 27 series. The selection was
based on the following criteria:
•
Substitutability. If two commodities are close
substitutes only one was included. For
Following the decomposition analysis, prices
were grouped into six broad categories, each of
which contained at least three series: Energy (coal,
crude oil, and natural gas); base metals
(aluminum, copper, lead, nickel, tin, and zinc);
precious metals (gold, platinum, and silver);
fertilizers (phosphate rock, potassium chlorate,
TSP, and urea); annual agriculture (cotton, maize,
soybean meal, soybean oil, rice, and wheat);
perennial agriculture (cocoa, coffee Arabica, coffee
Robusta, natural rubber, and tea).
Decomposition results are reported in table SF. I.
The numbers in the square brackets of the first
column represent weights and add to 100 for each
commodity group, subject to rounding. The shares
of each component add to 100, subject to
rounding. For example, coal's shares are: 0.36 +
0.42 + 0.18 + 0.04 = 1. The penultimate column
reports the parameter estimate from the regression
of Tt on a time trend while the last column reports
the Root Mean Square Error (RMSE)-a proxy
for nonlinearity.
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S P EC IAL FO CU S
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ANNEX TABLE SF.1 Real commodity price decomposition
Share of variance explained by
Tt
Ct[8-20]
C[2-8]
t
Trend
Number of cycles
Ct[8-20]
St
Ct[2-8]
β
RMSE
ENERGY
Coal [4.6]
0.36
0.42
0.18
0.04
3
11
0.43
5.31
Crude oil [84.6]
0.31
0.54
0.11
0.04
2
12
1.02
7.65
Natural gas [10.8]
0.19
0.68
0.10
0.03
2
11
0.57
2.50
AVERAGE
0.29
0.55
0.13
0.04
2
11
0.95
6.99
Aluminum [32.9]
0.57
0.20
0.20
0.03
4
10
-0.14
0.64
Copper [47.4]
0.47
0.30
0.19
0.04
3
9
-0.80
3.31
Lead [2.2]
0.57
0.25
0.16
0.02
3
8
-0.54
4.75
Nickel [9.9]
0.18
0.44
0.34
0.04
3
11
-0.78
1.63
Tin [2.6]
0.74
0.19
0.06
0.01
3
12
0.05
4.38
Zinc [5.0]
0.25
0.22
0.46
0.07
3
8
-0.09
2.08
AVERAGE
0.46
0.27
0.24
0.04
3
10
-0.52
2.46
Gold [77.8]
0.62
0.27
0.10
0.01
3
8
1.28
5.38
Platinum [18.9]
0.22
0.48
0.23
0.06
3
11
-0.22
1.85
Silver [3.3]
0.47
0.36
0.13
0.03
3
11
0.27
13.47
AVERAGE
0.44
0.37
0.15
0.03
3
10
0.96
4.98
Phosphate [16.9]
0.37
0.30
0.25
0.07
3
9
-0.40
6.48
Potassium [20.1]
0.36
0.45
0.16
0.03
3
10
-0.46
3.43
TSP [21.7]
0.36
0.24
0.34
0.06
4
9
-0.52
3.91
Urea [41.3]
0.24
0.42
0.22
0.12
3
12
-0.02
4.44
AVERAGE
0.33
0.35
0.24
0.07
3
10
-0.28
4.47
Cotton [8.5]
0.80
0.07
0.11
0.02
3
13
-0.07
9.00
Maize [20.5]
0.70
0.16
0.11
0.03
3
10
-0.50
3.55
Rice [15.2]
0.63
0.19
0.14
0.04
3
9
-0.43
3.29
Soybean meal [29.0]
0.69
0.10
0.17
0.04
3
10
-0.48
3.48
Soybean oil [14.3]
0.66
0.16
0.15
0.03
3
11
-0.72
3.15
Wheat [12.5]
0.62
0.18
0.15
0.05
3
9
-0.42
2.60
AVERAGE
0.68
0.14
0.14
0.04
3
10
-0.47
3.78
Cocoa [25.6]
0.67
0.22
0.10
0.01
3
11
0.03
15.41
Coffee Arabica [15.7]
0.61
0.24
0.12
0.04
3
14
0.22
10.38
Coffee Robusta [15.7]
0.75
0.17
0.06
0.02
3
13
0.42
15.86
Natural Rubber [30.6]
0.31
0.43
0.23
0.03
3
10
-0.36
17.39
Tea [12.4]
0.78
0.07
0.12
0.03
3
13
-0.17
9.47
AVERAGE
0.62
0.23
0.13
0.03
3
12
-0.03
14.56
ALL AVERAGE
0.47
0.32
0.17
0.04
3
11
0.10
6.21
BASE METALS
PRECIOUS METALS
FERTILIZERS
ANNUAL AGRICULTURE
PERENNIAL AGRICULTURE
Source: World Bank.
Note: Description of terms appear in the text.
C O M M O D I T Y M A R K E T S O U T LO O K | O C TO B E R 2 0 2 0
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